Pixel-Based Intraframe Prediction for Screen Content Encoding
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Solution Overview
Problem
Existing video compression technologies face challenges in accurately predicting pixel values within images, particularly for Screen Content images, due to the limitations of traditional intraframe prediction methods that use pixel blocks, which lead to errors and reduced accuracy.
Innovation Solution
The proposed method segments pixels into blocks and uses a pixel-based intraframe prediction approach, rearranging pixels to ensure that only reconstructed pixels are used for prediction, thereby avoiding error diffusion and improving prediction accuracy by treating each pixel as a unit for template matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional block-based intraframe prediction is used, then encoding complexity is reduced, but prediction accuracy deteriorates due to error diffusion
Solution Approach 1:
The patent segments the prediction process into two distinct phases: a first prediction pass that processes all pixels using template matching, and a second prediction pass that processes only abnormal pixels. This segmentation allows the system to achieve high prediction accuracy for critical pixels while avoiding the computational burden of applying the same intensive processing to all pixels, thus resolving the contradiction between accuracy and complexity.
Solution Approach 2:
The patent applies different prediction strategies to different pixels based on their characteristics. Normal pixels use simple reconstruction from encoded residuals, while abnormal pixels (identified by large residuals) receive specialized re-prediction processing. This local differentiation ensures high accuracy for pixels that need it while maintaining overall encoding efficiency, resolving the accuracy-complexity tradeoff.
2Measurement precision
If pixel-based prediction with rearranged pixels is used, then prediction accuracy is improved by avoiding error diffusion, but the risk of abnormal residuals increases
Solution Approach 1:
The patent performs a preliminary prediction pass before final encoding to identify abnormal pixels. By detecting pixels with large residuals in advance, the system can apply corrective re-prediction processing specifically to these abnormal pixels. This preliminary identification action ensures that reliability is maintained by correcting potential errors before they propagate, while the overall system benefits from the accuracy improvements of pixel-based prediction.
Solution Approach 2:
The patent implements a feedback mechanism where the results of the first prediction pass are used to identify abnormal pixels, which then trigger a second prediction pass. The encoded information about abnormal pixels and their re-prediction results is fed back into the decoding process, ensuring that both encoder and decoder produce identical results. This feedback loop maintains reliability by ensuring consistent reconstruction while preserving the accuracy benefits of pixel-based prediction.
3Measurement precision
If re-prediction processing is applied to abnormal pixels, then encoding accuracy is improved, but processing time increases
Solution Approach 1:
The patent applies the computationally intensive re-prediction processing only to a subset of pixels identified as abnormal, rather than applying it to all pixels. By using a threshold-based identification criterion (pixels with residuals exceeding a certain magnitude), the system performs partial processing only where necessary, significantly reducing the total processing time while maintaining high encoding accuracy for the critical abnormal pixels.
Data Source
AI summary
An image encoding method, decoding method and corresponding device, and intraframe pixel prediction method. The image encoding method comprises: a step of pixel segmentation, segmenting pixels in an image frame; a step of pixel value prediction, respectively performing a pixel value prediction process to obtain a first prediction value for each of pixels in a current block to be encoded; a step of residual calculation, calculating a residual for each of the pixels in the current block to be encoded; a step of discrete cosine transform, quantization and entropy encoding, performing discrete cosine transform, quantization and entropy encoding with respect to a residual block corresponding to the current block to be encoded obtained in the residual calculation step, wherein the quantized residual block is used in a pixel value reconstruction step at an encoding end, and the entropy encoded residual block is sent to a decoding end; and a pixel value reconstruction step, reconstructing a pixel value of the previously-encoded pixel, wherein the re-constructed pixel value is used in the pixel value prediction step. The residual calculation step comprises: calculating a first residual with respect to a pixel on the basis of the first prediction value of the pixel predicted in the pixel value prediction step and an actual value of the pixel; determining whether the first residual of the pixel is a normal residual or an abnormal residual; correcting the abnormal residual if the first residual of the pixel is an abnormal residual, the correction including recording a position of which the abnormal residual of the pixel has occurred; re-predicting the pixel to obtain a second prediction value and a corresponding second residual, and recording the re-prediction information, such that the pixel value reconstruction step of the encoding end and the decoding end can both reconstruct and decode the pixel value of the pixel on the basis of the position of which the abnormal residual of the pixel has occurred and the re-prediction information, wherein the normal residual block of the current block is formed by the residual of the pixel of the current block to be encoded after undergoing the abnormal residual correction, and is provided for further processing in the discrete cosine transform, quantization and entropy encoding step; separately encoding the position of which the abnormal residual of the pixel has occurred and the re-prediction information, wherein the encoding process is lossless, and the encoded pixel position and the re-prediction information are used in the pixel value reconstruction step and sent to the decoding end. Pixels can be re-arranged before segmentation, thereby avoiding error diffusion. In the pixel value prediction process, a prediction algorithm can be predicted first, and the pixel value is then predicted according to the determined prediction algorithm. By classifying the pixel residual into the normal residual and the abnormal residual, as well as by performing a re-prediction of the pixel of the abnormal residual, the accuracy of image encoding/decoding can be improved.